Mark Bedau

Metaphysics traditionally presumes a fundamental distinction between kinds (properties, classes, abstract universals) and particulars (concrete individuals). Whereas kinds and classes have members, for example, individuals have parts. This paper contrasts the kind/individual distinction with a different but equally fundamental distinction between explainers and non-explainers. It is often presumed that kinds are explainers and individuals are non-explainers. This paper defends a contrary thesis—explanatory individualism—according to which some explainers are concrete individuals, and it explores how this thesis is connected to the thesis of biological species individualism, according to which biological species are concrete individuals rather than kinds or classes.

Proceedings from the ninth International Conference on Artificial Life; papers by scientists of many disciplines focusing on the principles of organization and applications of complex, life-like systems. Artificial Life is an interdisciplinary effort to investigate the fundamental properties of living systems through the simulation and synthesis of life-like processes. The young field brings a powerful set of tools to the study of how high-level behavior can arise in systems governed by simple rules of interaction. Some of the fundamental questions include: What are the principles of evolution, learning, and growth that can be understood well enough to simulate as an information process? Can robots be built faster and more cheaply by mimicking biology than by the product design process used for automobiles and airplanes? How can we unify theories from dynamical systems, game theory, evolution, computing, geophysics, and cognition? The field has contributed fundamentally to our understanding of life itself through computer models, and has led to novel solutions to complex real-world problems across high technology and human society. This elite biennial meeting has grown from a small workshop in Santa Fe to a major international conference. This ninth volume of the proceedings of the international A-life conference reflects the growing quality and impact of this interdisciplinary scientific community.

Synthetic biology has spawned a debate about how society and the international community should go about policy‐making, especially given the potential for both transformative benefits and existential threats. One of the significant contributions of “The Ethics of Synthetic Biology: Next Steps and Prior Questions,” by Kaebnick, Gusmano, and Murray, is its exploration of the difficulties of devel­oping policy that appropriately addresses the risks and benefits of synthetic biology. In this comment I want to develop this point further and emphasize how the proper methodology for addressing synthetic biology's ethical and public policy issues are affected by the unpredictable and complex causal webs in synthetic biology (which have analogs in other new and emerging technologies).

The robust behavior of the patent citation network is a complex target of recent bottom-up models in science. This paper investigates the purpose and testing of three especially simple bottom-up models of the citation count distribution observed in the patent citation network. The complex causal webs in the models generate weakly emergent patterns of behavior, and this explains both the need for empirical observation of computer simulations of the models and the epistemic harmlessness of the resulting epistemic opacity.

The concept of living technology can be applied to any technology that is powerful and useful specifically because it has some of the fundamental features of living systems. This article is a brief general overview of living technology's current state and projected future. After illustrating living technology and discussing why it is complicated to define, I explain how it is related to so-called NBIC convergence (see below) and discuss some of the larger social, ethical and aesthetic issues that it raises.

There is a long history of cryptographic hash functions, i.e. functions mapping variable-length strings to fixed-length strings, and such functions are also expected to enjoy certain security properties. Hash functions can be effected via modular arithmetic, permutation-based schemes, chaotic mixing, and so on. Herein we introduce the notion of an artificial-life (ALife) hash function (ALHF), whereby the requisite mixing action of a good hash function is accomplished via ALife rules that give rise to complex evolution of a given system. Various security tests have been run, and the results reported for examples of ALHFs.

We describe a novel Internet-based method for building consensus and clarifying con icts in large stakeholder groups facing complex issues, and we use the method to survey and map the scienti c and organizational perspectives of the arti cial life community during the Seventh International Conference on Arti cial Life (summer 2000). The issues addressed in this survey included arti cial life’s main successes, main failures, main open scienti c questions, and main strategies for the future, as well as the bene ts and pitfalls of creating a professional society for arti cial life. By illuminating the arti cial life community’s collective perspective on these issues, this survey illustrates the value of such methods of harnessing the collective intelligence of large stakeholder groups.

Bringing together the latest scientific advances and some of the most enduring subtle philosophical puzzles and problems, this book collects original historical and contemporary sources to explore the wide range of issues surrounding the nature of life. Selections ranging from Aristotle and Descartes to Sagan and Dawkins are organised around four broad themes covering classical discussions of life, the origins and extent of natural life, contemporary artificial life creations and the definition and meaning of 'life' in its most general form. Each section is preceded by an extensive introduction connecting the various ideas discussed in individual chapters and providing helpful background material for understanding them. With its interdisciplinary perspective, this fascinating collection is essential reading for scientists and philosophers interested in astrobiology, synthetic biology and the philosophy of life.

Top-down synthetic biology makes partly synthetic cells by redesigning simple natural forms of life, and bottom-up synthetic biology aims to make fully synthetic cells using only entirely nonliving components. Within synthetic biology the notions of complexity and emergence are quite controversial, but the imprecision of key notions makes the discussion inconclusive. I employ a precise notion of weak emergent property, which is a robust characteristic of the behavior of complex bottom-up causal webs, where a complex causal web is one that is incompressible and its behavior cannot be derived except by crawling through all of the gory details of the interactions in the web. The central thesis of this article is that synthetic biology centrally is the activity of engineering the desired weak emergent properties of synthetic cells. Synthetic biology has many different ways to engineer desired weak emergent properties of synthetic cells, including Edisonian trial and error, standardized parts, refactoring, and reprogramming synthetic genomes. The article ends by noting two philosophical consequences of engineering weak emergence. One is epistemological: synthesis is crucial for discovering weak emergent properties. The other is metaphysical: simple life forms are nothing but complex chemical mechanisms.

The nature and status of cultural evolution and its connection with biological evolution are controversial in part because of Richard Dawkin’s suggestion that the scientific study of culture should include “memetics,” an analog of genetics in which genes are replaced by “memes”—the hypothetical units of cultural evolution. Memetics takes different forms; I focus on its minimal form, which claims merely that natural selection shapes to some extent the evolution of some aspects of culture. Advocates and critics of memetics disagree about the scientific status of memetics, but they agree that memetics must face the following fundamental problems. Problem 1: Cultural evolution differs too much from biological evolution. Problem 2: Culture is too complex. Problem 3: Memes are too difficult to identify and track. Problem 4: Memetics produces only trivial results. This paper examines these problems in the context of a minimal memetic analysis in one specific context: patented inventions. Technology is a special subset of culture, and patented inventions are a special subset of technology—not least because there is a detailed written record of every patent. I describe four recent empirical results on technological innovation derived from memetic analysis of the patent record. Result 1: Inkjet printing, PCR, and stents are key drivers of technological innovation. Result 2: Patent genealogies are tangled and incestuous. Result 3: Door-opening innovations drive the evolution of technology. Result 4: The evolving content of the drivers of innovation confirms the importance of inkjet printing, PCR, and stents, among other inventions. These results show that minimal memetics can provide a novel and illuminating analysis the evolution of patented technology. Furthermore, this memetic analysis can answer all of the main problems with memetics. Problem 1 can be dismissed because culture and biology can be quite disanalogous, provided that natural selection still operates in both. Problem 2 is a mirage, because memetic analysis of the patented inventions is consistent with the full richness and complexity of the evolution of technology. Problem 3 is easy to solve, because the patent record makes it trivial to identify and track patents and their key traits through lineages. Problem 4 can be fully answered only after memetic analysis becomes widespread, but the results reviewed here shows that minimal memetics does yield scientific results that are nontrivial and interesting.

This paper describes and defends the view that minimal chemical life essentially involves the chemical integration of three chemical functionalities: containment, metabolism, and program. This view is illustrated and explained with the help of CMP and Rasmussen diagrams in Protocells: bridging nonliving and living matter, 71–100, 2009b), both of which represent the key chemical functional dependencies among containment, metabolism, and program. The CMP model of minimal chemical life gains some support from the broad view of life as open-ended evolution, which I have defended elsewhere. Further support comes from the natural way the CMP model resolves the puzzle about whether life is a matter of degree.

This paper describes and defends the view that minimal chemical life essentially involves the chemical integration of three chemical functionalities: containment, metabolism, and program (Rasmussen et al. in Protocells: bridging nonliving and living matter, 2009a ). This view is illustrated and explained with the help of CMP and Rasmussen diagrams (Rasmussen et al. In: Rasmussen et al. (eds.) in Protocells: bridging nonliving and living matter, 71–100, 2009b ), both of which represent the key chemical functional dependencies among containment, metabolism, and program. The CMP model of minimal chemical life gains some support from the broad view of life as open-ended evolution, which I have defended elsewhere (Bedau in The philosophy of artificial life, 1996 ; Bedau in Artificial Life, 4:125–140, 1998 ). Further support comes from the natural way the CMP model resolves the puzzle about whether life is a matter of degree.

Artificial life uses computer models to study the essential nature of the characteristic processes of complex adaptive systems proceses such as self-organization, adaptation, and evolution. Work in the field is guided by the working hypothesis that simple computer models can capture the essential nature of these processes. This hypothesis is illustrated by recent results with a simple population of computational agents whose sensorimotor functionality undergo open-ended adaptive evolution. These might illuminate three aspects of complex adaptive systems in general: punctuated equilibrium dynamics of diversity, a transition separating genetic order and disorder, and a law of adaptive evolutionary activity.

Those interested in the relationship betw een environment structure and behavior — the topic of this special issue of Adaptive Behavior — w ill find much of value in Peter Godfrey-Smith's new book, Complexity and the Function of Mind in Nature (hereafter CFMN; all page citations are to CFMN unless otherw ise indicated). The w riting is clear and concise, aptly balancing precision and breadth, and a host of relevant issues are raised and advanced. Although my comments here w ill focus only on the book's fundamental conceptual framew ork for how organisms relate to their environments, I enthusiastically recommend the entire book.

We study the effects of environmental catastrophes on the evolution of a population of sensory-motor agents with individually evolving mutation rates, and compare these effects in a variety of control systems. A catastrophe makes the balance shift toward the need for evolutionary novelty, and we observe the mutation rate evolve upwards. As the population adapts the sensory-motor strategies to the new environment and the balance shifts toward a need for evolutionary memory, the mutation rate falls. These observations support the hypothesis that second-order evolution of the mutation flexibly balances the need for evolutionary “novelty” and “memory,” both of which are controlled by the mutation rate.